Pfannkuchensack · Oct 18, 2026 · Oct 18, 2026 · Oct 18, 2026 · Oct 18, 2026 · Oct 18, 2026
diff --git a/docs/src/content/docs/Users Guide/03.Models/02.model-families.mdx b/docs/src/content/docs/Users Guide/03.Models/02.model-families.mdx
@@ -1,7 +1,7 @@
 ---
 title: Model Formats and Families
 description: An overview of the models InvokeAI supports — checkpoint, Diffusers and quantized formats, the components that make up a model, and the model families with their licenses.
-lastUpdated: 2026-09-30
+lastUpdated: 2026-10-18
 sidebar:
   order: 2
 ---
@@ -118,7 +118,7 @@ faster generation.
 | **SDXL** | Images | Higher-resolution successor to SD 1.5 (1024×1024) with a similarly rich ecosystem of add-ons. An optional refiner model, used in the workflow editor, polishes fine detail. | OpenRAIL++-M; varies by fine-tune | [SDXL](/users-guide/models/local-models/sdxl/)  |
 | **Stable Diffusion 3.5** | Images | Medium and Large transformer models from Stability AI, with three text encoders. | Community, free under $1M revenue | [SD 3.5](/users-guide/models/local-models/sd-3/)  |
 | **FLUX.1** | Images | Dev, Schnell, Kontext (image editing) and Krea variants, plus Fill (inpainting, workflow editor only) and Redux, with ControlNets and IP-Adapters. | schnell: Apache 2.0; others non-commercial | [FLUX.1](/users-guide/models/local-models/flux-1/)  |
-| **FLUX.2** | Images | Klein 4B and 9B, and the much larger [dev]. Generates and edits images from reference images. | Klein 4B: Apache 2.0; Klein 9B and [dev] non-commercial | [FLUX.2](/users-guide/models/local-models/flux-2/)  |
+| **FLUX.2** | Images | Klein 4B and 9B, and the much larger [dev]. Generates and edits images from reference images; [dev] also takes a ControlNet. | Klein 4B: Apache 2.0; Klein 9B and [dev] non-commercial | [FLUX.2](/users-guide/models/local-models/flux-2/)  |
 | **CogView4** | Images | THUDM's 6B text-to-image model with a GLM text encoder. Basic support, without LoRAs, ControlNets or reference images. | Apache 2.0 | [CogView4](/users-guide/models/local-models/cogview4/)  |
 | **Z-Image** | Images | 6B model in a fast, few-step Turbo variant and a Base variant. Understands English and Chinese prompts, with ControlNets. | Apache 2.0 | [Z-Image](/users-guide/models/local-models/z-image/)  |
 | **ERNIE-Image** | Images | Baidu's 8B text-to-image model, in standard and distilled Turbo variants. | Apache 2.0 | [ERNIE-Image](/users-guide/models/local-models/ernie-image/)  |

diff --git a/docs/src/content/docs/Users Guide/03.Models/03.model-format-support.mdx b/docs/src/content/docs/Users Guide/03.Models/03.model-format-support.mdx
@@ -1,7 +1,7 @@
 ---
 title: Model Format Support
 description: Which file formats and quantizations InvokeAI loads for every model family, text encoder, VAE and adapter.
-lastUpdated: 2026-10-16
+lastUpdated: 2026-10-18
 sidebar:
   order: 3
 ---
@@ -101,8 +101,8 @@ not check, so a quantized file there fails with an unclear error or decodes inco
 | SD 1.x / 2.x | ✓ (LyCORIS, Diffusers) | ✓ | IP-Adapter, T2I-Adapter (SD 1.x), textual inversion |
 | SDXL | ✓ (LyCORIS, Diffusers, OMI) | ✓ | IP-Adapter, T2I-Adapter, textual inversion |
 | FLUX.1 | ✓ (LyCORIS, Diffusers, OMI) | ✓ | Control LoRA, IP-Adapter, Redux |
-| FLUX.2, Z-Image | ✓ (LyCORIS, Diffusers) | Z-Image only | |
-| Qwen-Image, Krea-2, Wan 2.2, Anima | ✓ (LyCORIS/kohya, including LoKR where noted on the family page) | Anima (ControlNet-LLLite) | |
+| FLUX.2, Z-Image | ✓ (LyCORIS, Diffusers) | FLUX.2 [dev] (single-file checkpoint), Z-Image | |
+| Qwen-Image, Krea-2, Wan 2.2, Anima | ✓ (LyCORIS/kohya, including LoKR where noted on the family page) | Qwen-Image (single-file checkpoint), Anima (ControlNet-LLLite) | |
 | LTX-2, MiniMax H3 | ✓ (plain low-rank; LoKR, LoHA and DoRA are refused) | ✗ | |
 | SD 3, CogView4, Ideogram 4, ERNIE-Image, Qwen-Image-2.1 | ✗ | ✗ | |
 

diff --git a/docs/src/content/docs/Users Guide/03.Models/Local Models/flux-2.mdx b/docs/src/content/docs/Users Guide/03.Models/Local Models/flux-2.mdx
@@ -1,7 +1,7 @@
 ---
 title: FLUX.2
-description: Generate and edit images with FLUX.2 Klein (4B and 9B, distilled and Base) and FLUX.2 [dev], including multi-reference image editing.
-lastUpdated: 2026-10-16
+description: Generate and edit images with FLUX.2 Klein (4B and 9B, distilled and Base) and FLUX.2 [dev], including multi-reference image editing and the FLUX.2 [dev] Fun-ControlNet-Union.
+lastUpdated: 2026-10-18
 sidebar:
   order: 5
 ---
@@ -34,7 +34,7 @@ Base models need 28 steps, distilled ones 4.
 | FLUX.2 Klein 9B | FLUX Non-Commercial License | The weights may not be used commercially; generated images may, except to train a competing model | Yes, on Black Forest Labs' repositories |
 | FLUX.2 [dev] | FLUX [dev] Non-Commercial License | As for Klein 9B | Yes, on Black Forest Labs' repositories |
 
-The Qwen3 and Mistral text encoders are Apache 2.0. Some repackaged copies show a different license in their metadata; the original model's license is the one that applies.
+The Qwen3 and Mistral text encoders are Apache 2.0. The FLUX.2 [dev] ControlNet Union is released under the FLUX [dev] Non-Commercial License, like FLUX.2 [dev] itself. Some repackaged copies show a different license in their metadata; the original model's license is the one that applies.
 
 This is a summary, not legal advice. Read the full license on the model's HuggingFace page before using a model commercially.
 
@@ -98,6 +98,7 @@ fp8 weights instead of expanding them.
 | FLUX.2 [dev] (Diffusers) | Diffusers pipeline | ~80 GB |
 | FLUX.2 [dev] (Diffusers, NF4) | NF4-quantized transformer and text encoder | ~18 GB VRAM with offload |
 | FLUX.2 [dev] Transformer (GGUF Q3_K_M / Q4_K_M / Q5_K_M / Q6_K / Q8_0) | GGUF | ~15.9 / 20 / 24 / 27.9 / 35.5 GB |
+| FLUX.2 [dev] ControlNet Union | bf16 single file; see [ControlNet](#controlnet) | ~8.2 GB |
 
 The GGUF transformers need a separate Mistral encoder. Q3_K_M and Q4_K_M install the GGUF Q4 encoder, the
 larger quants the GGUF Q8 encoder. Other encoder starters are the Comfy-Org builds — *FP8* (~18 GB, best
@@ -127,8 +128,8 @@ Selecting a FLUX.2 model applies these defaults:
 - **Size** — width and height must be multiples of 16.
 - **Negative prompt** — not available in the Generate tab or on the Canvas.
 
-Text-to-image, image-to-image, inpainting and outpainting all work on the Canvas. FLUX.2 has no ControlNet
-or IP-Adapter support.
+Text-to-image, image-to-image, inpainting and outpainting all work on the Canvas. FLUX.2 [dev] takes a
+[ControlNet](#controlnet); Klein models take none, and FLUX.2 has no IP-Adapter support.
 
 ## Reference images
 
@@ -138,6 +139,42 @@ Generate tab or the Canvas and describe the result you want in the prompt. No ex
 In the workflow editor, wrap each image in a **Kontext Conditioning - FLUX** node and connect it (or a
 collection of them) to the **Reference Images** input of **FLUX2 Denoise**.
 
+## ControlNet
+
+The **FLUX.2 [dev] ControlNet Union** starter model is alibaba-pai's *Fun-ControlNet-Union* for FLUX.2 [dev]
+(~8.2 GB, FLUX [dev] Non-Commercial License). One model handles every condition: **Canny**, **HED**, **Depth**,
+**Pose**, **MLSD**, **Scribble** and **Gray** control images, plus **inpainting**. The starter model installs
+`FLUX.2-dev-Fun-Controlnet-Union-2602.safetensors`, the build to use: Scribble and Gray exist only in it, and the
+repository's earlier file lost FLUX.2 [dev]'s CFG distillation during control training and performs worse, which the
+2602 build restores. It works with FLUX.2 [dev] only:
+the Klein transformers are narrower than the one it was trained beside. With a Klein model selected, a control
+layer's settings and the **Invoke** button say that the ControlNet is not compatible, and nothing is generated until
+the layer is disabled or the model changed.
+
+On the Canvas, add a **Control Layer** while a FLUX.2 [dev] model is selected. Its adapter type is **FLUX.2 [dev]
+ControlNet** and its pixels are the control image; the layer's **Filter** turns a raster into one of the conditions
+(Canny, HED, Depth Anything, DW Openpose, MLSD, Scribble or Grayscale). The layer's **Weight** is the model's control
+scale: it ranges from `0` to `2`, starts at `0.75`, and `0.65` to `0.80` is the recommended range. **Step range**
+limits the steps the control applies to. **Only one** FLUX.2 [dev] ControlNet layer can be used per generation, and
+it can be combined with reference images.
+
+When the Canvas inpaints or outpaints with a control layer present, the ControlNet also receives the image being
+regenerated and the mask of the region as its inpainting condition. Without a control layer, inpainting and
+outpainting are guided by the inpaint mask alone.
+
+In the workflow editor, the same thing is the **FLUX.2 [dev] ControlNet** node feeding the **Control** input of
+**FLUX2 Denoise**. Give it a control **Image**, an **Inpaint Image** together with its **Inpaint Mask** (white is
+regenerated), or both. Its **Control Scale**, **Begin Step Percent** and **End Step Percent** are the layer's weight
+and step range. The images are resized to the generation size and encoded with the VAE connected to **FLUX2
+Denoise**; **Tiled** and **Tile Size** tile that encode, and an untiled encode that runs out of memory is retried in
+tiles. **FLUX2 Denoise** stops with a message when the ControlNet meets a Klein model.
+
+:::note[Memory]
+The ControlNet's 8.2 GB of weights stay loaded beside the [dev] transformer for the whole generation, and its
+blocks add activation memory that grows with the image size and the number of reference images. On a GPU that
+cannot hold all of it, Invoke keeps part of the models in system RAM, and each step is slower.
+:::
+
 ## Regional guidance
 
 Regional guidance layers with a prompt are supported on the Canvas. Regional reference images are not.
@@ -164,7 +201,8 @@ Decode](/users-guide/image-generation/advanced-topics/pid-decode/).
 | --- | --- |
 | **Main Model - Flux2 Klein** / **Main Model - FLUX.2 [dev]** | Loads the transformer, encoder and VAE |
 | **Prompt - Flux2 Klein** / **Prompt - FLUX.2 [dev]** | Encodes the prompt |
-| **FLUX2 Denoise** | Runs the diffusion; takes the VAE and optional reference images |
+| **FLUX2 Denoise** | Runs the diffusion; takes the VAE, optional reference images and, for [dev], a ControlNet |
+| **FLUX.2 [dev] ControlNet** | Configures the ControlNet Union: control image and/or inpaint image with mask, scale, step range |
 | **Latents to Image - FLUX2** / **Image to Latents - FLUX2** | VAE decode / encode |
 
 **FLUX2 Denoise** also has a **CFG Scale** and a negative conditioning input, which the Generate tab leaves

diff --git a/docs/src/content/docs/Users Guide/03.Models/Local Models/qwen-image.mdx b/docs/src/content/docs/Users Guide/03.Models/Local Models/qwen-image.mdx
@@ -1,7 +1,7 @@
 ---
 title: Qwen Image
-description: Generate and edit images with the Qwen Image 2512 text-to-image model and the Qwen Image Edit 2511 reference-image editing model, including GGUF installs and the Lightning LoRAs.
-lastUpdated: 2026-10-16
+description: Generate and edit images with the Qwen Image 2512 text-to-image model and the Qwen Image Edit 2511 reference-image editing model, including GGUF installs, the Lightning LoRAs and the Fun-ControlNet-Union.
+lastUpdated: 2026-10-18
 sidebar:
   order: 8
 ---
@@ -17,11 +17,13 @@ variants:
   person in image 2").
 
 The variant is detected automatically on install. Both variants can also run text-to-image,
-image-to-image, inpainting and outpainting on the Canvas; only the Edit variant accepts reference images.
+image-to-image, inpainting and outpainting on the Canvas; only the Edit variant accepts reference images,
+and only the text-to-image variant takes a [ControlNet](#controlnet).
 
 ## License
 
-Qwen Image 2512, Qwen Image Edit 2511, the Lightning LoRAs and the Qwen2.5-VL text encoder are released under **Apache 2.0**, which allows commercial use. None of the downloads is gated.
+Qwen Image 2512, Qwen Image Edit 2511, the Lightning LoRAs, the Qwen2.5-VL text encoder and the Qwen Image
+ControlNet Union are released under **Apache 2.0**, which allows commercial use. None of the downloads is gated.
 
 This is a summary, not legal advice. Read the full license on the model's HuggingFace page before using a model commercially.
 
@@ -135,6 +137,29 @@ Image**; connect an **Image to Latents - Qwen Image** node to the **Reference La
 Qwen Image LoRAs (diffusers PEFT, Kohya and LoKR formats) are supported and apply to the transformer.
 In the workflow editor use **Apply LoRA - Qwen Image** or **Apply LoRA Collection - Qwen Image**.
 
+## ControlNet
+
+The **Qwen Image ControlNet Union** starter model is alibaba-pai's *Fun-ControlNet-Union* for Qwen Image 2512
+(~3.5 GB, Apache 2.0). One model handles every condition: **Canny**, **HED**, **Depth**, **Pose**, **MLSD**,
+**Scribble** and **Gray** control images, plus **inpainting**. It is trained for the text-to-image transformer:
+with a Qwen Image Edit model selected, a control layer's settings and the **Invoke** button say that the
+ControlNet is not compatible, and nothing is generated until the layer is disabled or the model changed.
+
+On the Canvas, add a **Control Layer** while a Qwen Image model is selected. Its adapter type is **Qwen Image
+ControlNet** and its pixels are the control image; the layer's **Filter** turns a raster into one of the
+conditions (Canny, HED, Depth Anything, DW Openpose, MLSD, Scribble or Grayscale). The layer's **Weight** is
+the model's control scale: it ranges from `0` to `2`, starts at `0.85`, and `0.70` to `0.95` is the
+recommended range. **Only one** Qwen Image control layer can be used per generation.
+
+When the Canvas inpaints or outpaints with a control layer present, the ControlNet also receives the image being
+regenerated and the mask of the region as its inpainting condition. Without a control layer, inpainting and
+outpainting work as before.
+
+In the workflow editor, the same thing is the **Qwen Image ControlNet** node feeding the **Control** input of
+**Denoise - Qwen Image**. Give it a control **Image**, an **Inpaint Image** together with its **Inpaint Mask**
+(white is regenerated), or both. **Denoise - Qwen Image** then also needs its **VAE** input connected, which it
+uses to encode these images.
+
 ## PiD super-resolution decode
 
 Qwen Image works with [PiD Decode](/users-guide/image-generation/advanced-topics/pid-decode/), which replaces the VAE
@@ -147,7 +172,8 @@ Decoder Qwen-Image (2K to 4K)* decoders (including an int8 build of the latter)
 | ------------------------------------------- | ------------------------------------------------------------------- |
 | **Main Model - Qwen Image**                 | Loads the transformer, VAE and Qwen VL encoder (or a component source) |
 | **Prompt - Qwen Image**                     | Encodes the prompt and any reference images                         |
-| **Denoise - Qwen Image**                    | Runs sampling; accepts reference latents, img2img latents and masks |
+| **Denoise - Qwen Image**                    | Runs sampling; accepts reference latents, img2img latents, masks and a ControlNet |
+| **Qwen Image ControlNet**                   | Configures the ControlNet Union: control image and/or inpaint image with mask, scale, step range |
 | **Image to Latents - Qwen Image**           | VAE encode                                                          |
 | **Latents to Image - Qwen Image**           | VAE decode                                                          |
 | **Latents to Image - Qwen-Image + PiD (4x SR)** | PiD super-resolution decode                                     |

diff --git a/docs/src/content/docs/Users Guide/03.Models/Local Models/z-image.mdx b/docs/src/content/docs/Users Guide/03.Models/Local Models/z-image.mdx
@@ -107,18 +107,28 @@ Two Z-Image ControlNets are available as starters (both are part of the bundle):
 - **Z-Image ControlNet Tile** is useful for upscaling and adding detail. The **Upscale** tool can use it as an
   optional anchor; see [Upscaling](/users-guide/image-generation/upscale/).
 
+Every Z-Image Turbo Fun-ControlNet alibaba-pai has published can be installed from its `.safetensors` file:
+the first Union release, Union 2.0, the Union and Tile 2.1 builds (8-step, 2601 and 2602 included) and the 2.1
+Lite builds. Invoke tells them apart by their weights. Invoke does not inpaint through a Z-Image ControlNet:
+a control layer takes a control image only.
+
 On the Canvas, add a **Control Layer** while a Z-Image model is selected. The layer uses a Z-Image
 ControlNet with a default weight of `0.75`. The weight ranges from `0` to `2`, and `0.65` to `0.80` is the
 recommended range. **Only one** Z-Image control layer can be used per generation.
 
+Earlier Invoke versions placed the hints of the Lite and first Union builds after the wrong layers, and left
+out the refiner hints of 2.0 and 2.1 (2.0 also refined its control through the wrong blocks). Applied as they were trained, these ControlNets now follow the control image
+more strongly at the same weight; lower the weight if a control image constrains the result too much.
+
 In the workflow editor, the same thing is the **Z-Image ControlNet** node feeding the **Control** input of
 **Denoise - Z-Image**. That node also needs the **VAE** input connected, which it uses to encode the
 control image.
 
 ## Regional prompting
 
-Z-Image supports **Regional Guidance** layers on the Canvas with **positive** prompts. Regional negative
-prompts, auto-negative and regional reference images are not supported for Z-Image.
+Z-Image supports **Regional Guidance** layers on the Canvas with **positive** prompts, together with a
+control layer if you like. Regional negative prompts, auto-negative and regional reference images are not
+supported for Z-Image.
 
 In the workflow editor, **Prompt - Z-Image** takes an optional mask, and **Denoise - Z-Image** accepts
 either one conditioning or a collection of them.

diff --git a/docs/src/content/docs/Users Guide/07.Canvas/02.canvas-guide.mdx b/docs/src/content/docs/Users Guide/07.Canvas/02.canvas-guide.mdx
@@ -1,7 +1,7 @@
 ---
 title: Canvas guide
 description: A detailed guide to the Canvas — its tools and their options, navigation, the header buttons, the generation frame, selections, transform, filters, the staging area, menus, settings and keyboard shortcuts.
-lastUpdated: 2026-10-05
+lastUpdated: 2026-10-18
 ---
 
 import { Image } from 'astro:assets';
@@ -117,7 +117,7 @@ To crop a layer to the generation frame, choose **Crop layer to bbox** from its
 * **Edge detection** — Canny, HED, Lineart, Lineart Anime, MLSD, PiDiNet and Scribble.
 * **Depth & normal** — Depth Anything and Normal map.
 * **Pose & face** — DW Openpose and Mediapipe Face.
-* **Color & tone** — Color map and Adjust image.
+* **Color & tone** — Color map, Adjust image and Grayscale.
 * **Blur & noise** — Content shuffle, Blur and Noise.
 * **Upscale** — an upscaling model.
 

diff --git a/docs/src/content/docs/configuration/Optimization/low-vram-mode.mdx b/docs/src/content/docs/configuration/Optimization/low-vram-mode.mdx
@@ -210,8 +210,8 @@ To always decode untiled unless you ask for tiling, turn this off. A decode too
 auto_tiled_decode: false
 ```
 
-- **Always tile:** set `force_tiled_decode: true` in `invokeai.yaml`. It covers the VAE decode and encode for SD1.5/SDXL, FLUX.1, FLUX.2, Z-Image, Qwen-Image and Qwen-Image-2.1, the Anima encode, the control image of a Z-Image ControlNet, and the Krea-2 style reference. Other model families (for example SD3, Wan and LTX-2) ignore it.
-- **Per node:** the SD, FLUX.1, FLUX.2, Z-Image, Qwen-Image and Qwen-Image-2.1 **Latents to Image** and **Image to Latents** nodes, and **Image to Latents - Anima**, have **Tiled** and **Tile Size** fields for workflows. So does the **Z-Image ControlNet** node, for the control image the denoise encodes. The [Upscale panel](/users-guide/image-generation/upscale/) turns tiling on by itself.
+- **Always tile:** set `force_tiled_decode: true` in `invokeai.yaml`. It covers the VAE decode and encode for SD1.5/SDXL, FLUX.1, FLUX.2, Z-Image, Qwen-Image and Qwen-Image-2.1, the Anima encode, the control image of a Z-Image ControlNet, the control and inpaint images of a Qwen Image ControlNet and of a FLUX.2 [dev] ControlNet, and the Krea-2 style reference. Other model families (for example SD3, Wan and LTX-2) ignore it.
+- **Per node:** the SD, FLUX.1, FLUX.2, Z-Image, Qwen-Image and Qwen-Image-2.1 **Latents to Image** and **Image to Latents** nodes, and **Image to Latents - Anima**, have **Tiled** and **Tile Size** fields for workflows. So do the **Z-Image ControlNet**, **Qwen Image ControlNet** and **FLUX.2 [dev] ControlNet** nodes, for the images the denoise encodes. The [Upscale panel](/users-guide/image-generation/upscale/) turns tiling on by itself.
 - **Automatic retry:** if a FLUX.1, FLUX.2, Z-Image or Anima decode, or a FLUX.1 or FLUX.2 encode, runs out of memory, InvokeAI retries it once with tiling and logs that it did.
 
 A tiled decode is not pixel-identical to a single-pass one. The VAE looks at the whole image at once, so the difference is spread over the image rather than limited to the tile seams; it is small (for a 1024x1024 FLUX.2 Klein image, 5.6 of 255 per pixel value on average, with no visible seams), but the same seed will not reproduce an untiled result exactly.